[Calango] is a railway technician, and for a school final project created the Rail Wear Surveillance Trolley (RWST) which is a delightfully designed device made mainly from PVC conduit with one job: travel down a segment of train track while shining a green laser onto the rail, and capture camera images. The trolley holds both the laser and the camera at just the right angles for the camera to capture a profile of the rail’s curved surface. The images are sent via Bluetooth to a smartphone for later analysis. Rail wear can be judged by checking how well the profile of the rail conforms to the ideal profile of an unworn segment. The trolley is manually pushed by an operator, but [Calango] says that ideally, it would be self-propelled and able to inspect a length of the track then return on its own.
The project was made on a tight budget, which led to some clever solutions like using a rotary encoder attached to a wheel as a makeshift distance sensor. If things get desperate enough, it’s even possible to roll your own rotary encoder with a 3D printer and two microswitches.
[Neumi] wrote in with a sweet robotics hack. It’s a 2D laser distance sensor (YouTube) made with a cheap line laser and an optical mouse’s flow-sensor chip used as a low-resolution camera. In one sense, it’s a standard laser-distance-sensor project. But it is clever for a whole bunch of reasons.
For one, using a mouse sensor as a low-res camera is awesome. It’s designed to read from a standard red LED, so the sensitivity is in just the right ballpark for use with a line laser. It returns a 30×30 pixel greyscale image, which is just about the right amount of data for a low-end microcontroller to handle and keep up with the framerate without resorting to coding tricks.
It’s also no coincidence that these sensors are available with lenses built in, for relatively cheap, on eBay. Apparently the quadcopter gurus use them as if they were mice to visually track their quad’s motion. Hacker spillover!
Detecting the laser line as it reflects off of whatever objects are lying on [Neumi]’s floor could also possibly prove difficult, and might produce false readings in the presence of background illumination. So [Neumi] takes two readings with the camera — one with the laser on and one with it off — and differences them. Done fast enough, this should reduce any non-laser sources down to the sensor’s noise floor. Finally, there’s some thresholding and averaging going on behind the scenes that help make everything work out right. The code is up on GitHub.
Not a bad build for a 2D laser distance system on a budget. If you want to shell out a bit more money, and are into a seriously involved build, this is probably the slickest we’ve seen in a long time. And if you’re thinking that you’ve heard of [Neumi] before, you’re right: we featured this 405mm laser PCB exposer / burner CNC machine just a few months ago.
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